HCI 660 Benchmark – Health Information Technologies
Health Information Technologies Benchmark Technology adoption in the healthcare profession has had a tremendous impact on healthcare delivery and patient happiness. Many hospitals throughout the world have built electronic health records (HER), which have resulted in a significant improvement in the services available. The incorporation of technology has primarily resulted in improved treatments, equipment, and medicine. Medical practitioners have been able to deliver more thorough care to patients as a result of improved equipment, which has resulted in better treatments. Better therapies have improved the quality of life for persons suffering from a variety of long-term health disorders as a result of this.
The contact with patients has enhanced because to technological advancements. In general, doctors have been able to access patient records through technology, allowing them to provide more detailed medical information to specific patients. The adoption of this technology is critical since it allows patients to receive individualized therapies. Patients’ records can be transcribed and made available to both patients and doctors via the internet. With the growing demand for data in medical research, technology has proven to be a boon in terms of data acquisition, storage, analysis, and administration (Morilla et al., 2017). The enhanced ability to store and retrieve data is one of the advantages of technology. Furthermore, current healthcare operational systems have established interconnected systems known as interoperability, which improves the speedy transfer of patient information amongst healthcare providers by allowing data to be shared. Healthcare organizations have been able to accomplish medication safety through greater readability, which could potentially reduce medication errors, thanks to the use of technology in the management of patient data.
Databases Available Online That Were Considered in the VLab
The VLab activity took into account a number of distinct databases. These databases were primarily used for data capture, storage, and presentation. In most circumstances, data presentation is required to arrive at reliable study conclusions. HCUPnet and WISQARS are two databases that include a vast amount of data that may be retrieved and used in research. WISQARS is an interactive, online database that contains information on violent death, fatal and nonfatal injuries, and injury costs (Chen & Warner, 2018). HCUPnet, on the other hand, is a free online inquiry system that primarily incorporates information from the Healthcare Cost and Utilization Project (HCUP). Different healthcare statistics for inpatient, ambulatory services, emergency rooms, and population-based healthcare data for regions, counties, states, and the country are available in the database. HCUPnet was used to quickly and easily research a variety of research topics during the VLab activity, including quality care and patient safety, variation in medical practices, utilization by special populations, in-hospital mortality for diagnoses and procedures, as well as trends in inpatient and outpatient charges, access, and outcomes (McDermott et al., 2017). The databases HCUPnet and WISQARS aided in the retrieval and presentation of data.
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In the research process, data presentation is critical; it graphically highlights the information found in figures, graphs, charts, and even tables. The presentation of data necessitates complex procedures aimed at delivering crucial or important information gleaned from the investigation. The way data is presented is crucial for establishing clarity by disclosing facts gleaned through the research process (Diong et al., 2018). The audience can readily follow and absorb the offered information, which is why most academics prefer graphical tables and charts. Tables are always accompanied with figures that depict the results of the data analysis operations. There are various graphs, tables, and charts in the Tableau VLab Activity that have been utilized to depict information from the data analysis process.
Also Read: What are the role of benchmarks in quality improvement activities? In order to benchmark progress, describe what an organization can compare its benchmarks against. Provide an example of a source for benchmarks
Application and Use of Health Information Technologies
Health Data Management Tools, Processes, and Structures
Health information technology, tools, applications, procedures, and structures were used to handle health data during the VLab Activity. The EHR system was one of the health information technologies used. The system was primarily used for healthcare data entry, retrieval, and presentation. Through an interoperability approach, the EHR systems were linked to the two databases, HCUPnet and WISQARS. A variety of applications was used to assist in the transmission of data and other healthcare information into the databases mentioned above. Computer networks, servers, and artificial intelligence are just a few of the instruments that were used. These technologies were primarily incorporated to improve information sharing and understanding in order to inform decision-making processes. The adoption of this technology is critical since it allows patients to receive individualized therapies. Patients’ records can be transcribed and made available to both patients and doctors via the internet.
The Most Frequently Used Analytics Technologies
Organizations that provide health care
There are certain common technologies that are used by a variety of healthcare organizations. Various tools have simplified the analysis and presentation of data for decision-making processes at these healthcare organizations. Structured Query Language (SQL), as well as data analysis tools like R, STATA, and SPSS, are examples of these specific technologies. Data visualization software and Java are two other options. Healthcare organizations can achieve high efficiency in the administration of healthcare data when these tools are used effectively.
As demonstrated above, the data from table 1 was utilized to create histograms and bar graphs. The tables above can be readily seen using the chart. The percentages or proportions computed from the tables were used to create the charts. The graphs were created using Microsoft Excel, with each bar reflecting the data in each column (Cockerill et al., 2018). The preceding charts were created with Microsoft Excel using pre-existing functions or built-in functions (Menge et al., 2018). Readers may quickly visualize the data and make accurate descriptions or predictions based on the factors used by looking at the chart.
L. H. Chen and M. Warner (2018). Injury morbidity is being monitored. In the field of injury research (pp. 23-43). Boston, MA: Springer. https://link.springer.com/chapter/10.1007/978-1-4614-1599-2 2
M. Cockerill, N. Craig, and A. Thurston (2018). Using Social Interdependence Theory as a Model for Data Analysis and Presentation, teachers’ perceptions of the impact of peer learning in their classrooms. 14-27 in the International Journal of Education and Practice, vol. 6, no. 1. http://www.conscientiabeam.com/journal/61 retrieved from http://www.conscientiabeam.com/journal/61
J. Diong, A. A. Butler, S. C. Gandevia, and M. E. Héroux (2018). Despite editorial advice, poor statistical reporting, data presentation, and spin remain. e0202121, PloS one, 13(8). The article can be found at https://doi.org/10.1371/journal.pone.0202121.
K. W. McDermott, A. J. Weiss, and A. Elixhauser (2017). Burn-related hospital inpatient stays and ER visits in 2013, statistics brief# 217. https://europepmc.org/article/nbk/nbk409513
Menge, D. N., MacPherson, A. C., Bytnerowicz, T. A., Quebbeman, A. W., Schwartz, N. B., Taylor, B. N., and Wolf, A. A. Menge, D. N., MacPherson, A. C., Bytnerowicz, T. A., Quebbeman, A. W., Schwartz, N. B., Taylor, B. N (2018). In the presentation of ecological data, logarithmic scales might lead to misinterpretation. 1393-1402 in Nature Ecology & Evolution, 2(9). https://www.nature.com/articles/s41559-018-0610-7
M. D. R. Morilla, M. Sans, A. Casasa, and N. Giménez (2017). Physicians’ perspectives on implementing technology in healthcare. 17(1), 92, BMC medical informatics and decision making. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-017-0489-2